A system of product recommendations was created based on a dataset provided, which contained the product purchases from a wide range of clients. The system itself takes a client ID, and returns a list of recommended products. Two different algorithms are offered: The first is a collaborative based filtering method, which creates a rank for each product purchased by each client; the second is a content based method using NLP to detect similarity between product titles. The resulting recommendations are provided with a categorical weighted average. Keywords: Collaborative filtering, item based, Artificial Intelligence

For having more information about the project and the methodology, please see the document "Report.pdf" in the root of the project

This application is made with the framework React

1. First, you need to go to the front directory cd /app

2. Then you need to install all dependencies npm install

3. After the project installation you can launch the app npm start

The infrastructure is made in Python with Flask framework

1. First, you need to go to the infrastructure directory cd /server

2. Then, you need to install all dependencies pip install -r requirements.txt

3. If you have any missing module during the installtion. Just run the command pip install name_module

4. After the project installation is complete, you can launch the app python run.py